#include <stdio.h>
#include "opencv2/core/internal.hpp"
-
#if CV_SSE2 || CV_SSE3
# if !CV_SSE4_1 && !CV_SSE4_2
# define _mm_blendv_pd(a, b, m) _mm_xor_pd(a, _mm_and_pd(_mm_xor_pd(b, a), m))
# endif
#endif
-# if CV_AVX
-# define CV_HAAR_USE_AVX 1
-# else
-# if CV_SSE2 || CV_SSE3
-# define CV_HAAR_USE_SSE 1
-# endif
-# endif
+#if CV_AVX
+# define CV_HAAR_USE_AVX 1
+#else
+# if CV_SSE2 || CV_SSE3
+# define CV_HAAR_USE_SSE 1
+# endif
+#endif
/* these settings affect the quality of detection: change with care */
#define CV_ADJUST_FEATURES 1
float weight;
}
rect[CV_HAAR_FEATURE_MAX];
-}
-CvHidHaarFeature;
+} CvHidHaarFeature;
typedef struct CvHidHaarTreeNode
float threshold;
int left;
int right;
-}
-CvHidHaarTreeNode;
+} CvHidHaarTreeNode;
typedef struct CvHidHaarClassifier
//CvHaarFeature* orig_feature;
CvHidHaarTreeNode* node;
float* alpha;
-}
-CvHidHaarClassifier;
+} CvHidHaarClassifier;
typedef struct CvHidHaarStageClassifier
struct CvHidHaarStageClassifier* next;
struct CvHidHaarStageClassifier* child;
struct CvHidHaarStageClassifier* parent;
-}
-CvHidHaarStageClassifier;
+} CvHidHaarStageClassifier;
-struct CvHidHaarClassifierCascade
+typedef struct CvHidHaarClassifierCascade
{
int count;
int isStumpBased;
sumtype *p0, *p1, *p2, *p3;
void** ipp_stages;
-};
+} CvHidHaarClassifierCascade;
const int icv_object_win_border = 1;
}
-//AVX version icvEvalHidHaarClassifier. Process 8 CvHidHaarClassifiers per call. Check AVX support before invocation!!
+// AVX version icvEvalHidHaarClassifier. Process 8 CvHidHaarClassifiers per call. Check AVX support before invocation!!
#ifdef CV_HAAR_USE_AVX
CV_INLINE
double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
double variance_norm_factor, size_t p_offset )
{
int CV_DECL_ALIGNED(32) idxV[8] = {0,0,0,0,0,0,0,0};
- char flags[8] = {0,0,0,0,0,0,0,0};
+ uchar flags[8] = {0,0,0,0,0,0,0,0};
CvHidHaarTreeNode* nodes[8];
double res = 0;
- char exitConditionFlag = 0;
+ uchar exitConditionFlag = 0;
for(;;)
{
- float CV_DECL_ALIGNED(32) tmp[8] = {0,0,0,0,0,0,0,0};
- nodes[0] = classifier ->node + idxV[0];
+ float CV_DECL_ALIGNED(32) tmp[8] = {0,0,0,0,0,0,0,0};
+ nodes[0] = (classifier+0)->node + idxV[0];
nodes[1] = (classifier+1)->node + idxV[1];
nodes[2] = (classifier+2)->node + idxV[2];
nodes[3] = (classifier+3)->node + idxV[3];
nodes[7] = (classifier+7)->node + idxV[7];
__m256 t = _mm256_set1_ps(variance_norm_factor);
- t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,nodes[6]->threshold,nodes[5]->threshold,nodes[4]->threshold,nodes[3]->threshold,nodes[2]->threshold,nodes[1]->threshold,nodes[0]->threshold));
- __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0],p_offset), calc_sum(nodes[6]->feature.rect[0],p_offset), calc_sum(nodes[5]->feature.rect[0],p_offset),
- calc_sum(nodes[4]->feature.rect[0],p_offset), calc_sum(nodes[3]->feature.rect[0],p_offset), calc_sum(nodes[2]->feature.rect[0],p_offset), calc_sum(nodes[1]->feature.rect[0],
- p_offset),calc_sum(nodes[0]->feature.rect[0],p_offset));
- __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight, nodes[6]->feature.rect[0].weight, nodes[5]->feature.rect[0].weight,
- nodes[4]->feature.rect[0].weight, nodes[3]->feature.rect[0].weight, nodes[2]->feature.rect[0].weight, nodes[1]->feature.rect[0].weight, nodes[0]->feature.rect[0].weight);
- __m256 sum = _mm256_mul_ps(offset, weight);
+ t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
+ nodes[6]->threshold,
+ nodes[5]->threshold,
+ nodes[4]->threshold,
+ nodes[3]->threshold,
+ nodes[2]->threshold,
+ nodes[1]->threshold,
+ nodes[0]->threshold));
+
+ __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
+ calc_sum(nodes[6]->feature.rect[0], p_offset),
+ calc_sum(nodes[5]->feature.rect[0], p_offset),
+ calc_sum(nodes[4]->feature.rect[0], p_offset),
+ calc_sum(nodes[3]->feature.rect[0], p_offset),
+ calc_sum(nodes[2]->feature.rect[0], p_offset),
+ calc_sum(nodes[1]->feature.rect[0], p_offset),
+ calc_sum(nodes[0]->feature.rect[0], p_offset));
+
+ __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
+ nodes[6]->feature.rect[0].weight,
+ nodes[5]->feature.rect[0].weight,
+ nodes[4]->feature.rect[0].weight,
+ nodes[3]->feature.rect[0].weight,
+ nodes[2]->feature.rect[0].weight,
+ nodes[1]->feature.rect[0].weight,
+ nodes[0]->feature.rect[0].weight);
- offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1],p_offset),calc_sum(nodes[6]->feature.rect[1],p_offset),calc_sum(nodes[5]->feature.rect[1],p_offset),
- calc_sum(nodes[4]->feature.rect[1],p_offset),calc_sum(nodes[3]->feature.rect[1],p_offset),calc_sum(nodes[2]->feature.rect[1],p_offset),calc_sum(nodes[1]->feature.rect[1],p_offset),
- calc_sum(nodes[0]->feature.rect[1],p_offset));
- weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight, nodes[6]->feature.rect[1].weight, nodes[5]->feature.rect[1].weight, nodes[4]->feature.rect[1].weight,
- nodes[3]->feature.rect[1].weight, nodes[2]->feature.rect[1].weight, nodes[1]->feature.rect[1].weight, nodes[0]->feature.rect[1].weight);
+ __m256 sum = _mm256_mul_ps(offset, weight);
- sum = _mm256_add_ps(sum, _mm256_mul_ps(offset,weight));
+ offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
+ calc_sum(nodes[6]->feature.rect[1], p_offset),
+ calc_sum(nodes[5]->feature.rect[1], p_offset),
+ calc_sum(nodes[4]->feature.rect[1], p_offset),
+ calc_sum(nodes[3]->feature.rect[1], p_offset),
+ calc_sum(nodes[2]->feature.rect[1], p_offset),
+ calc_sum(nodes[1]->feature.rect[1], p_offset),
+ calc_sum(nodes[0]->feature.rect[1], p_offset));
+
+ weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
+ nodes[6]->feature.rect[1].weight,
+ nodes[5]->feature.rect[1].weight,
+ nodes[4]->feature.rect[1].weight,
+ nodes[3]->feature.rect[1].weight,
+ nodes[2]->feature.rect[1].weight,
+ nodes[1]->feature.rect[1].weight,
+ nodes[0]->feature.rect[1].weight);
+
+ sum = _mm256_add_ps(sum, _mm256_mul_ps(offset, weight));
if( nodes[0]->feature.rect[2].p0 )
- tmp[0] = calc_sum(nodes[0]->feature.rect[2],p_offset) * nodes[0]->feature.rect[2].weight;
+ tmp[0] = calc_sum(nodes[0]->feature.rect[2], p_offset) * nodes[0]->feature.rect[2].weight;
if( nodes[1]->feature.rect[2].p0 )
- tmp[1] = calc_sum(nodes[1]->feature.rect[2],p_offset) * nodes[1]->feature.rect[2].weight;
+ tmp[1] = calc_sum(nodes[1]->feature.rect[2], p_offset) * nodes[1]->feature.rect[2].weight;
if( nodes[2]->feature.rect[2].p0 )
- tmp[2] = calc_sum(nodes[2]->feature.rect[2],p_offset) * nodes[2]->feature.rect[2].weight;
+ tmp[2] = calc_sum(nodes[2]->feature.rect[2], p_offset) * nodes[2]->feature.rect[2].weight;
if( nodes[3]->feature.rect[2].p0 )
- tmp[3] = calc_sum(nodes[3]->feature.rect[2],p_offset) * nodes[3]->feature.rect[2].weight;
+ tmp[3] = calc_sum(nodes[3]->feature.rect[2], p_offset) * nodes[3]->feature.rect[2].weight;
if( nodes[4]->feature.rect[2].p0 )
- tmp[4] = calc_sum(nodes[4]->feature.rect[2],p_offset) * nodes[4]->feature.rect[2].weight;
+ tmp[4] = calc_sum(nodes[4]->feature.rect[2], p_offset) * nodes[4]->feature.rect[2].weight;
if( nodes[5]->feature.rect[2].p0 )
- tmp[5] = calc_sum(nodes[5]->feature.rect[2],p_offset) * nodes[5]->feature.rect[2].weight;
+ tmp[5] = calc_sum(nodes[5]->feature.rect[2], p_offset) * nodes[5]->feature.rect[2].weight;
if( nodes[6]->feature.rect[2].p0 )
- tmp[6] = calc_sum(nodes[6]->feature.rect[2],p_offset) * nodes[6]->feature.rect[2].weight;
+ tmp[6] = calc_sum(nodes[6]->feature.rect[2], p_offset) * nodes[6]->feature.rect[2].weight;
if( nodes[7]->feature.rect[2].p0 )
- tmp[7] = calc_sum(nodes[7]->feature.rect[2],p_offset) * nodes[7]->feature.rect[2].weight;
+ tmp[7] = calc_sum(nodes[7]->feature.rect[2], p_offset) * nodes[7]->feature.rect[2].weight;
sum = _mm256_add_ps(sum,_mm256_load_ps(tmp));
- __m256 left = _mm256_set_ps(nodes[7]->left,nodes[6]->left,nodes[5]->left,nodes[4]->left,nodes[3]->left,nodes[2]->left,nodes[1]->left,nodes[0]->left);
+ __m256 left = _mm256_set_ps(nodes[7]->left, nodes[6]->left, nodes[5]->left, nodes[4]->left, nodes[3]->left, nodes[2]->left, nodes[1]->left, nodes[0]->left );
__m256 right = _mm256_set_ps(nodes[7]->right,nodes[6]->right,nodes[5]->right,nodes[4]->right,nodes[3]->right,nodes[2]->right,nodes[1]->right,nodes[0]->right);
- _mm256_store_si256((__m256i*)idxV,_mm256_cvttps_epi32(_mm256_blendv_ps(right, left,_mm256_cmp_ps(sum, t, _CMP_LT_OQ ))));
+ _mm256_store_si256((__m256i*)idxV, _mm256_cvttps_epi32(_mm256_blendv_ps(right, left, _mm256_cmp_ps(sum, t, _CMP_LT_OQ))));
for(int i = 0; i < 8; i++)
{
if(!flags[i])
{
exitConditionFlag++;
- flags[i]=1;
- res+=((classifier+i)->alpha[-idxV[i]]);
+ flags[i] = 1;
+ res += (classifier+i)->alpha[-idxV[i]];
}
idxV[i]=0;
}
}
- if(exitConditionFlag==8)
+ if(exitConditionFlag == 8)
return res;
}
}
-#endif
+#endif //CV_HAAR_USE_AVX
CV_INLINE
double icvEvalHidHaarClassifier( CvHidHaarClassifier* classifier,
cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
CvPoint pt, double& stage_sum, int start_stage )
{
- #ifdef CV_HAAR_USE_AVX
- bool haveAVX = false;
- if(cv::checkHardwareSupport(CV_CPU_AVX))
- if(__xgetbv()&0x6)// Check if the OS will save the YMM registers
- {
- haveAVX = true;
- }
- #else
- #ifdef CV_HAAR_USE_SSE
- bool haveSSE2 = cv::checkHardwareSupport(CV_CPU_SSE2);
- #endif
- #endif
+#ifdef CV_HAAR_USE_AVX
+ bool haveAVX = false;
+ if(cv::checkHardwareSupport(CV_CPU_AVX))
+ if(__xgetbv()&0x6)// Check if the OS will save the YMM registers
+ haveAVX = true;
+#else
+# ifdef CV_HAAR_USE_SSE
+ bool haveSSE2 = cv::checkHardwareSupport(CV_CPU_SSE2);
+# endif
+#endif
int p_offset, pq_offset;
int i, j;
while( ptr )
{
stage_sum = 0.0;
+ j = 0;
- #ifdef CV_HAAR_USE_AVX
+#ifdef CV_HAAR_USE_AVX
if(haveAVX)
{
- for( ; j < cascade->stage_classifier[i].count-8; j+=8 )
+ for( ; j <= ptr->count - 8; j += 8 )
{
stage_sum += icvEvalHidHaarClassifierAVX(
- cascade->stage_classifier[i].classifier+j,
+ ptr->classifier + j,
variance_norm_factor, p_offset );
}
}
- #endif
- for( j = 0; j < ptr->count; j++ )
+#endif
+ for( ; j < ptr->count; j++ )
{
stage_sum += icvEvalHidHaarClassifier( ptr->classifier + j, variance_norm_factor, p_offset );
}
}
else if( cascade->isStumpBased )
{
- #ifdef CV_HAAR_USE_AVX
- if(haveAVX)
+#ifdef CV_HAAR_USE_AVX
+ if(haveAVX)
+ {
+ CvHidHaarClassifier* classifiers[8];
+ CvHidHaarTreeNode* nodes[8];
+ for( i = start_stage; i < cascade->count; i++ )
{
- CvHidHaarClassifier* classifiers[8];
- CvHidHaarTreeNode* nodes[8];
- for( i = start_stage; i < cascade->count; i++ )
+ stage_sum = 0.0;
+ j = 0;
+ float CV_DECL_ALIGNED(32) buf[8];
+ if( cascade->stage_classifier[i].two_rects )
{
- stage_sum = 0.0;
- j = 0;
- float CV_DECL_ALIGNED(32) buf[8];
- if( cascade->stage_classifier[i].two_rects )
+ for( ; j <= cascade->stage_classifier[i].count - 8; j += 8 )
{
- for( ; j <= cascade->stage_classifier[i].count-8; j+=8 )
- {
- //__m256 stage_sumPart = _mm256_setzero_ps();
- classifiers[0] = cascade->stage_classifier[i].classifier + j;
- nodes[0] = classifiers[0]->node;
- classifiers[1] = cascade->stage_classifier[i].classifier + j + 1;
- nodes[1] = classifiers[1]->node;
- classifiers[2] = cascade->stage_classifier[i].classifier + j + 2;
- nodes[2]= classifiers[2]->node;
- classifiers[3] = cascade->stage_classifier[i].classifier + j + 3;
- nodes[3] = classifiers[3]->node;
- classifiers[4] = cascade->stage_classifier[i].classifier + j + 4;
- nodes[4] = classifiers[4]->node;
- classifiers[5] = cascade->stage_classifier[i].classifier + j + 5;
- nodes[5] = classifiers[5]->node;
- classifiers[6] = cascade->stage_classifier[i].classifier + j + 6;
- nodes[6] = classifiers[6]->node;
- classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
- nodes[7] = classifiers[7]->node;
-
- __m256 t = _mm256_set1_ps(variance_norm_factor);
- t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,nodes[6]->threshold,nodes[5]->threshold,nodes[4]->threshold,nodes[3]->threshold,nodes[2]->threshold,nodes[1]->threshold,nodes[0]->threshold));
-
- __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0],p_offset), calc_sum(nodes[6]->feature.rect[0],p_offset), calc_sum(nodes[5]->feature.rect[0],p_offset),
- calc_sum(nodes[4]->feature.rect[0],p_offset), calc_sum(nodes[3]->feature.rect[0],p_offset), calc_sum(nodes[2]->feature.rect[0],p_offset), calc_sum(nodes[1]->feature.rect[0],
- p_offset),calc_sum(nodes[0]->feature.rect[0],p_offset));
- __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight, nodes[6]->feature.rect[0].weight, nodes[5]->feature.rect[0].weight,
- nodes[4]->feature.rect[0].weight, nodes[3]->feature.rect[0].weight, nodes[2]->feature.rect[0].weight, nodes[1]->feature.rect[0].weight, nodes[0]->feature.rect[0].weight);
- __m256 sum = _mm256_mul_ps(offset, weight);
-
- offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1],p_offset),calc_sum(nodes[6]->feature.rect[1],p_offset),calc_sum(nodes[5]->feature.rect[1],p_offset),
- calc_sum(nodes[4]->feature.rect[1],p_offset),calc_sum(nodes[3]->feature.rect[1],p_offset),calc_sum(nodes[2]->feature.rect[1],p_offset),calc_sum(nodes[1]->feature.rect[1],p_offset),
- calc_sum(nodes[0]->feature.rect[1],p_offset));
- weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight, nodes[6]->feature.rect[1].weight, nodes[5]->feature.rect[1].weight, nodes[4]->feature.rect[1].weight,
- nodes[3]->feature.rect[1].weight, nodes[2]->feature.rect[1].weight, nodes[1]->feature.rect[1].weight, nodes[0]->feature.rect[1].weight);
- sum = _mm256_add_ps(sum, _mm256_mul_ps(offset,weight));
-
- __m256 alpha0 = _mm256_set_ps(classifiers[7]->alpha[0],classifiers[6]->alpha[0],classifiers[5]->alpha[0],classifiers[4]->alpha[0],classifiers[3]->alpha[0],
- classifiers[2]->alpha[0],classifiers[1]->alpha[0],classifiers[0]->alpha[0]);
- __m256 alpha1 = _mm256_set_ps(classifiers[7]->alpha[1],classifiers[6]->alpha[1],classifiers[5]->alpha[1],classifiers[4]->alpha[1],classifiers[3]->alpha[1],
- classifiers[2]->alpha[1],classifiers[1]->alpha[1],classifiers[0]->alpha[1]);
-
- _mm256_store_ps(buf, _mm256_blendv_ps(alpha0, alpha1, _mm256_cmp_ps(t, sum, _CMP_LE_OQ )));
- stage_sum+=(buf[0]+buf[1]+buf[2]+buf[3]+buf[4]+buf[5]+buf[6]+buf[7]);
-
- }
+ classifiers[0] = cascade->stage_classifier[i].classifier + j;
+ nodes[0] = classifiers[0]->node;
+ classifiers[1] = cascade->stage_classifier[i].classifier + j + 1;
+ nodes[1] = classifiers[1]->node;
+ classifiers[2] = cascade->stage_classifier[i].classifier + j + 2;
+ nodes[2] = classifiers[2]->node;
+ classifiers[3] = cascade->stage_classifier[i].classifier + j + 3;
+ nodes[3] = classifiers[3]->node;
+ classifiers[4] = cascade->stage_classifier[i].classifier + j + 4;
+ nodes[4] = classifiers[4]->node;
+ classifiers[5] = cascade->stage_classifier[i].classifier + j + 5;
+ nodes[5] = classifiers[5]->node;
+ classifiers[6] = cascade->stage_classifier[i].classifier + j + 6;
+ nodes[6] = classifiers[6]->node;
+ classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
+ nodes[7] = classifiers[7]->node;
+
+ __m256 t = _mm256_set1_ps(variance_norm_factor);
+ t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
+ nodes[6]->threshold,
+ nodes[5]->threshold,
+ nodes[4]->threshold,
+ nodes[3]->threshold,
+ nodes[2]->threshold,
+ nodes[1]->threshold,
+ nodes[0]->threshold));
+
+ __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
+ calc_sum(nodes[6]->feature.rect[0], p_offset),
+ calc_sum(nodes[5]->feature.rect[0], p_offset),
+ calc_sum(nodes[4]->feature.rect[0], p_offset),
+ calc_sum(nodes[3]->feature.rect[0], p_offset),
+ calc_sum(nodes[2]->feature.rect[0], p_offset),
+ calc_sum(nodes[1]->feature.rect[0], p_offset),
+ calc_sum(nodes[0]->feature.rect[0], p_offset));
+
+ __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
+ nodes[6]->feature.rect[0].weight,
+ nodes[5]->feature.rect[0].weight,
+ nodes[4]->feature.rect[0].weight,
+ nodes[3]->feature.rect[0].weight,
+ nodes[2]->feature.rect[0].weight,
+ nodes[1]->feature.rect[0].weight,
+ nodes[0]->feature.rect[0].weight);
+
+ __m256 sum = _mm256_mul_ps(offset, weight);
+
+ offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
+ calc_sum(nodes[6]->feature.rect[1], p_offset),
+ calc_sum(nodes[5]->feature.rect[1], p_offset),
+ calc_sum(nodes[4]->feature.rect[1], p_offset),
+ calc_sum(nodes[3]->feature.rect[1], p_offset),
+ calc_sum(nodes[2]->feature.rect[1], p_offset),
+ calc_sum(nodes[1]->feature.rect[1], p_offset),
+ calc_sum(nodes[0]->feature.rect[1], p_offset));
+
+ weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
+ nodes[6]->feature.rect[1].weight,
+ nodes[5]->feature.rect[1].weight,
+ nodes[4]->feature.rect[1].weight,
+ nodes[3]->feature.rect[1].weight,
+ nodes[2]->feature.rect[1].weight,
+ nodes[1]->feature.rect[1].weight,
+ nodes[0]->feature.rect[1].weight);
+
+ sum = _mm256_add_ps(sum, _mm256_mul_ps(offset,weight));
+
+ __m256 alpha0 = _mm256_set_ps(classifiers[7]->alpha[0],
+ classifiers[6]->alpha[0],
+ classifiers[5]->alpha[0],
+ classifiers[4]->alpha[0],
+ classifiers[3]->alpha[0],
+ classifiers[2]->alpha[0],
+ classifiers[1]->alpha[0],
+ classifiers[0]->alpha[0]);
+ __m256 alpha1 = _mm256_set_ps(classifiers[7]->alpha[1],
+ classifiers[6]->alpha[1],
+ classifiers[5]->alpha[1],
+ classifiers[4]->alpha[1],
+ classifiers[3]->alpha[1],
+ classifiers[2]->alpha[1],
+ classifiers[1]->alpha[1],
+ classifiers[0]->alpha[1]);
+
+ _mm256_store_ps(buf, _mm256_blendv_ps(alpha0, alpha1, _mm256_cmp_ps(t, sum, _CMP_LE_OQ)));
+ stage_sum += (buf[0]+buf[1]+buf[2]+buf[3]+buf[4]+buf[5]+buf[6]+buf[7]);
+ }
- for( ; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
+ for( ; j < cascade->stage_classifier[i].count; j++ )
+ {
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
- double t = node->threshold*variance_norm_factor;
- double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
- sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
- stage_sum += classifier->alpha[sum >= t];
- }
+ double t = node->threshold*variance_norm_factor;
+ double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
+ sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
+ stage_sum += classifier->alpha[sum >= t];
}
- else
+ }
+ else
+ {
+ for( ; j <= (cascade->stage_classifier[i].count)-8; j+=8 )
{
- for( ; j <= (cascade->stage_classifier[i].count)-8; j+=8 )
- {
- float CV_DECL_ALIGNED(32) tmp[8] = {0,0,0,0,0,0,0,0};
-
- classifiers[0] = cascade->stage_classifier[i].classifier + j;
- nodes[0] = classifiers[0]->node;
- classifiers[1] = cascade->stage_classifier[i].classifier + j + 1;
- nodes[1] = classifiers[1]->node;
- classifiers[2] = cascade->stage_classifier[i].classifier + j + 2;
- nodes[2]= classifiers[2]->node;
- classifiers[3] = cascade->stage_classifier[i].classifier + j + 3;
- nodes[3] = classifiers[3]->node;
- classifiers[4] = cascade->stage_classifier[i].classifier + j + 4;
- nodes[4] = classifiers[4]->node;
- classifiers[5] = cascade->stage_classifier[i].classifier + j + 5;
- nodes[5] = classifiers[5]->node;
- classifiers[6] = cascade->stage_classifier[i].classifier + j + 6;
- nodes[6] = classifiers[6]->node;
- classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
- nodes[7] = classifiers[7]->node;
-
- __m256 t = _mm256_set1_ps(variance_norm_factor);
- t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,nodes[6]->threshold,nodes[5]->threshold,nodes[4]->threshold,nodes[3]->threshold,nodes[2]->threshold,nodes[1]->threshold,nodes[0]->threshold));
-
- __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0],p_offset), calc_sum(nodes[6]->feature.rect[0],p_offset), calc_sum(nodes[5]->feature.rect[0],p_offset),
- calc_sum(nodes[4]->feature.rect[0],p_offset), calc_sum(nodes[3]->feature.rect[0],p_offset), calc_sum(nodes[2]->feature.rect[0],p_offset), calc_sum(nodes[1]->feature.rect[0],
- p_offset),calc_sum(nodes[0]->feature.rect[0],p_offset));
- __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight, nodes[6]->feature.rect[0].weight, nodes[5]->feature.rect[0].weight,
- nodes[4]->feature.rect[0].weight, nodes[3]->feature.rect[0].weight, nodes[2]->feature.rect[0].weight, nodes[1]->feature.rect[0].weight, nodes[0]->feature.rect[0].weight);
- __m256 sum = _mm256_mul_ps(offset, weight);
-
- offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1],p_offset),calc_sum(nodes[6]->feature.rect[1],p_offset),calc_sum(nodes[5]->feature.rect[1],p_offset),
- calc_sum(nodes[4]->feature.rect[1],p_offset),calc_sum(nodes[3]->feature.rect[1],p_offset),calc_sum(nodes[2]->feature.rect[1],p_offset),calc_sum(nodes[1]->feature.rect[1],p_offset),
- calc_sum(nodes[0]->feature.rect[1],p_offset));
- weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight, nodes[6]->feature.rect[1].weight, nodes[5]->feature.rect[1].weight, nodes[4]->feature.rect[1].weight,
- nodes[3]->feature.rect[1].weight, nodes[2]->feature.rect[1].weight, nodes[1]->feature.rect[1].weight, nodes[0]->feature.rect[1].weight);
-
- sum = _mm256_add_ps(sum, _mm256_mul_ps(offset,weight));
-
- if( nodes[0]->feature.rect[2].p0 )
- tmp[0] = calc_sum(nodes[0]->feature.rect[2],p_offset) * nodes[0]->feature.rect[2].weight;
- if( nodes[1]->feature.rect[2].p0 )
- tmp[1] = calc_sum(nodes[1]->feature.rect[2],p_offset) * nodes[1]->feature.rect[2].weight;
- if( nodes[2]->feature.rect[2].p0 )
- tmp[2] = calc_sum(nodes[2]->feature.rect[2],p_offset) * nodes[2]->feature.rect[2].weight;
- if( nodes[3]->feature.rect[2].p0 )
- tmp[3] = calc_sum(nodes[3]->feature.rect[2],p_offset) * nodes[3]->feature.rect[2].weight;
- if( nodes[4]->feature.rect[2].p0 )
- tmp[4] = calc_sum(nodes[4]->feature.rect[2],p_offset) * nodes[4]->feature.rect[2].weight;
- if( nodes[5]->feature.rect[2].p0 )
- tmp[5] = calc_sum(nodes[5]->feature.rect[2],p_offset) * nodes[5]->feature.rect[2].weight;
- if( nodes[6]->feature.rect[2].p0 )
- tmp[6] = calc_sum(nodes[6]->feature.rect[2],p_offset) * nodes[6]->feature.rect[2].weight;
- if( nodes[7]->feature.rect[2].p0 )
- tmp[7] = calc_sum(nodes[7]->feature.rect[2],p_offset) * nodes[7]->feature.rect[2].weight;
-
- sum = _mm256_add_ps(sum, _mm256_load_ps(tmp));
-
- __m256 alpha0 = _mm256_set_ps(classifiers[7]->alpha[0],classifiers[6]->alpha[0],classifiers[5]->alpha[0],classifiers[4]->alpha[0],classifiers[3]->alpha[0],
- classifiers[2]->alpha[0],classifiers[1]->alpha[0],classifiers[0]->alpha[0]);
- __m256 alpha1 = _mm256_set_ps(classifiers[7]->alpha[1],classifiers[6]->alpha[1],classifiers[5]->alpha[1],classifiers[4]->alpha[1],classifiers[3]->alpha[1],
- classifiers[2]->alpha[1],classifiers[1]->alpha[1],classifiers[0]->alpha[1]);
-
- __m256 outBuf = _mm256_blendv_ps(alpha0, alpha1, _mm256_cmp_ps(t, sum, _CMP_LE_OQ ));
- outBuf = _mm256_hadd_ps(outBuf, outBuf);
- outBuf = _mm256_hadd_ps(outBuf, outBuf);
- _mm256_store_ps(buf, outBuf);
- stage_sum+=(buf[0]+buf[4]);//(buf[0]+buf[1]+buf[2]+buf[3]+buf[4]+buf[5]+buf[6]+buf[7]);
- }
+ float CV_DECL_ALIGNED(32) tmp[8] = {0,0,0,0,0,0,0,0};
+
+ classifiers[0] = cascade->stage_classifier[i].classifier + j;
+ nodes[0] = classifiers[0]->node;
+ classifiers[1] = cascade->stage_classifier[i].classifier + j + 1;
+ nodes[1] = classifiers[1]->node;
+ classifiers[2] = cascade->stage_classifier[i].classifier + j + 2;
+ nodes[2] = classifiers[2]->node;
+ classifiers[3] = cascade->stage_classifier[i].classifier + j + 3;
+ nodes[3] = classifiers[3]->node;
+ classifiers[4] = cascade->stage_classifier[i].classifier + j + 4;
+ nodes[4] = classifiers[4]->node;
+ classifiers[5] = cascade->stage_classifier[i].classifier + j + 5;
+ nodes[5] = classifiers[5]->node;
+ classifiers[6] = cascade->stage_classifier[i].classifier + j + 6;
+ nodes[6] = classifiers[6]->node;
+ classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
+ nodes[7] = classifiers[7]->node;
+
+ __m256 t = _mm256_set1_ps(variance_norm_factor);
+
+ t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
+ nodes[6]->threshold,
+ nodes[5]->threshold,
+ nodes[4]->threshold,
+ nodes[3]->threshold,
+ nodes[2]->threshold,
+ nodes[1]->threshold,
+ nodes[0]->threshold));
+
+ __m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
+ calc_sum(nodes[6]->feature.rect[0], p_offset),
+ calc_sum(nodes[5]->feature.rect[0], p_offset),
+ calc_sum(nodes[4]->feature.rect[0], p_offset),
+ calc_sum(nodes[3]->feature.rect[0], p_offset),
+ calc_sum(nodes[2]->feature.rect[0], p_offset),
+ calc_sum(nodes[1]->feature.rect[0], p_offset),
+ calc_sum(nodes[0]->feature.rect[0], p_offset));
+
+ __m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
+ nodes[6]->feature.rect[0].weight,
+ nodes[5]->feature.rect[0].weight,
+ nodes[4]->feature.rect[0].weight,
+ nodes[3]->feature.rect[0].weight,
+ nodes[2]->feature.rect[0].weight,
+ nodes[1]->feature.rect[0].weight,
+ nodes[0]->feature.rect[0].weight);
+
+ __m256 sum = _mm256_mul_ps(offset, weight);
+
+ offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
+ calc_sum(nodes[6]->feature.rect[1], p_offset),
+ calc_sum(nodes[5]->feature.rect[1], p_offset),
+ calc_sum(nodes[4]->feature.rect[1], p_offset),
+ calc_sum(nodes[3]->feature.rect[1], p_offset),
+ calc_sum(nodes[2]->feature.rect[1], p_offset),
+ calc_sum(nodes[1]->feature.rect[1], p_offset),
+ calc_sum(nodes[0]->feature.rect[1], p_offset));
+
+ weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
+ nodes[6]->feature.rect[1].weight,
+ nodes[5]->feature.rect[1].weight,
+ nodes[4]->feature.rect[1].weight,
+ nodes[3]->feature.rect[1].weight,
+ nodes[2]->feature.rect[1].weight,
+ nodes[1]->feature.rect[1].weight,
+ nodes[0]->feature.rect[1].weight);
+
+ sum = _mm256_add_ps(sum, _mm256_mul_ps(offset, weight));
+
+ if( nodes[0]->feature.rect[2].p0 )
+ tmp[0] = calc_sum(nodes[0]->feature.rect[2],p_offset) * nodes[0]->feature.rect[2].weight;
+ if( nodes[1]->feature.rect[2].p0 )
+ tmp[1] = calc_sum(nodes[1]->feature.rect[2],p_offset) * nodes[1]->feature.rect[2].weight;
+ if( nodes[2]->feature.rect[2].p0 )
+ tmp[2] = calc_sum(nodes[2]->feature.rect[2],p_offset) * nodes[2]->feature.rect[2].weight;
+ if( nodes[3]->feature.rect[2].p0 )
+ tmp[3] = calc_sum(nodes[3]->feature.rect[2],p_offset) * nodes[3]->feature.rect[2].weight;
+ if( nodes[4]->feature.rect[2].p0 )
+ tmp[4] = calc_sum(nodes[4]->feature.rect[2],p_offset) * nodes[4]->feature.rect[2].weight;
+ if( nodes[5]->feature.rect[2].p0 )
+ tmp[5] = calc_sum(nodes[5]->feature.rect[2],p_offset) * nodes[5]->feature.rect[2].weight;
+ if( nodes[6]->feature.rect[2].p0 )
+ tmp[6] = calc_sum(nodes[6]->feature.rect[2],p_offset) * nodes[6]->feature.rect[2].weight;
+ if( nodes[7]->feature.rect[2].p0 )
+ tmp[7] = calc_sum(nodes[7]->feature.rect[2],p_offset) * nodes[7]->feature.rect[2].weight;
+
+ sum = _mm256_add_ps(sum, _mm256_load_ps(tmp));
+
+ __m256 alpha0 = _mm256_set_ps(classifiers[7]->alpha[0],
+ classifiers[6]->alpha[0],
+ classifiers[5]->alpha[0],
+ classifiers[4]->alpha[0],
+ classifiers[3]->alpha[0],
+ classifiers[2]->alpha[0],
+ classifiers[1]->alpha[0],
+ classifiers[0]->alpha[0]);
+ __m256 alpha1 = _mm256_set_ps(classifiers[7]->alpha[1],
+ classifiers[6]->alpha[1],
+ classifiers[5]->alpha[1],
+ classifiers[4]->alpha[1],
+ classifiers[3]->alpha[1],
+ classifiers[2]->alpha[1],
+ classifiers[1]->alpha[1],
+ classifiers[0]->alpha[1]);
+
+ __m256 outBuf = _mm256_blendv_ps(alpha0, alpha1, _mm256_cmp_ps(t, sum, _CMP_LE_OQ ));
+ outBuf = _mm256_hadd_ps(outBuf, outBuf);
+ outBuf = _mm256_hadd_ps(outBuf, outBuf);
+ _mm256_store_ps(buf, outBuf);
+ stage_sum += (buf[0] + buf[4]);
+ }
- for( ; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
-
- double t = node->threshold*variance_norm_factor;
- double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
- sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
- if( node->feature.rect[2].p0 )
- sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
- stage_sum += classifier->alpha[sum >= t];
- }
+ for( ; j < cascade->stage_classifier[i].count; j++ )
+ {
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
+
+ double t = node->threshold*variance_norm_factor;
+ double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
+ sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
+ if( node->feature.rect[2].p0 )
+ sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
+ stage_sum += classifier->alpha[sum >= t];
}
- if( stage_sum < cascade->stage_classifier[i].threshold )
- return -i;
}
+ if( stage_sum < cascade->stage_classifier[i].threshold )
+ return -i;
}
- else
- #endif
- #if defined CV_HAAR_USE_SSE && CV_HAAR_USE_SSE && (!defined CV_HAAR_USE_AVX || !CV_HAAR_USE_AVX) //old SSE optimization
- if(haveSSE2)
+ }
+ else
+#elif defined CV_HAAR_USE_SSE //old SSE optimization
+ if(haveSSE2)
+ {
+ for( i = start_stage; i < cascade->count; i++ )
{
- for( i = start_stage; i < cascade->count; i++ )
+ __m128d vstage_sum = _mm_setzero_pd();
+ if( cascade->stage_classifier[i].two_rects )
{
- __m128d vstage_sum = _mm_setzero_pd();
- if( cascade->stage_classifier[i].two_rects )
+ for( j = 0; j < cascade->stage_classifier[i].count; j++ )
{
- for( j = 0; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
-
- // ayasin - NHM perf optim. Avoid use of costly flaky jcc
- __m128d t = _mm_set_sd(node->threshold*variance_norm_factor);
- __m128d a = _mm_set_sd(classifier->alpha[0]);
- __m128d b = _mm_set_sd(classifier->alpha[1]);
- __m128d sum = _mm_set_sd(calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight +
- calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight);
- t = _mm_cmpgt_sd(t, sum);
- vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
- }
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
+
+ // ayasin - NHM perf optim. Avoid use of costly flaky jcc
+ __m128d t = _mm_set_sd(node->threshold*variance_norm_factor);
+ __m128d a = _mm_set_sd(classifier->alpha[0]);
+ __m128d b = _mm_set_sd(classifier->alpha[1]);
+ __m128d sum = _mm_set_sd(calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight +
+ calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight);
+ t = _mm_cmpgt_sd(t, sum);
+ vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
}
- else
+ }
+ else
+ {
+ for( j = 0; j < cascade->stage_classifier[i].count; j++ )
{
- for( j = 0; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
- // ayasin - NHM perf optim. Avoid use of costly flaky jcc
- __m128d t = _mm_set_sd(node->threshold*variance_norm_factor);
- __m128d a = _mm_set_sd(classifier->alpha[0]);
- __m128d b = _mm_set_sd(classifier->alpha[1]);
- double _sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
- _sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
- if( node->feature.rect[2].p0 )
- _sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
- __m128d sum = _mm_set_sd(_sum);
-
- t = _mm_cmpgt_sd(t, sum);
- vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
- }
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
+ // ayasin - NHM perf optim. Avoid use of costly flaky jcc
+ __m128d t = _mm_set_sd(node->threshold*variance_norm_factor);
+ __m128d a = _mm_set_sd(classifier->alpha[0]);
+ __m128d b = _mm_set_sd(classifier->alpha[1]);
+ double _sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
+ _sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
+ if( node->feature.rect[2].p0 )
+ _sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
+ __m128d sum = _mm_set_sd(_sum);
+
+ t = _mm_cmpgt_sd(t, sum);
+ vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
}
- __m128d i_threshold = _mm_set1_pd(cascade->stage_classifier[i].threshold);
- if( _mm_comilt_sd(vstage_sum, i_threshold) )
- return -i;
}
+ __m128d i_threshold = _mm_set1_pd(cascade->stage_classifier[i].threshold);
+ if( _mm_comilt_sd(vstage_sum, i_threshold) )
+ return -i;
}
- else
- #endif
+ }
+ else
+#endif // AVX or SSE
+ {
+ for( i = start_stage; i < cascade->count; i++ )
{
- for( i = start_stage; i < cascade->count; i++ )
+ stage_sum = 0.0;
+ if( cascade->stage_classifier[i].two_rects )
{
- stage_sum = 0.0;
- if( cascade->stage_classifier[i].two_rects )
+ for( j = 0; j < cascade->stage_classifier[i].count; j++ )
{
- for( j = 0; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
- double t = node->threshold*variance_norm_factor;
- double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
- sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
- stage_sum += classifier->alpha[sum >= t];
- }
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
+ double t = node->threshold*variance_norm_factor;
+ double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
+ sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
+ stage_sum += classifier->alpha[sum >= t];
}
- else
+ }
+ else
+ {
+ for( j = 0; j < cascade->stage_classifier[i].count; j++ )
{
- for( j = 0; j < cascade->stage_classifier[i].count; j++ )
- {
- CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
- CvHidHaarTreeNode* node = classifier->node;
- double t = node->threshold*variance_norm_factor;
- double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
- sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
- if( node->feature.rect[2].p0 )
- sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
- stage_sum += classifier->alpha[sum >= t];
- }
+ CvHidHaarClassifier* classifier = cascade->stage_classifier[i].classifier + j;
+ CvHidHaarTreeNode* node = classifier->node;
+ double t = node->threshold*variance_norm_factor;
+ double sum = calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight;
+ sum += calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight;
+ if( node->feature.rect[2].p0 )
+ sum += calc_sum(node->feature.rect[2],p_offset) * node->feature.rect[2].weight;
+ stage_sum += classifier->alpha[sum >= t];
}
- if( stage_sum < cascade->stage_classifier[i].threshold )
- return -i;
}
+ if( stage_sum < cascade->stage_classifier[i].threshold )
+ return -i;
}
+ }
}
-
else
{
for( i = start_stage; i < cascade->count; i++ )
{
stage_sum = 0.0;
int k = 0;
- #ifdef CV_HAAR_USE_AVX
+
+#ifdef CV_HAAR_USE_AVX
if(haveAVX)
{
- for( ; k < cascade->stage_classifier[i].count-8; k+=8 )
+ for( ; k < cascade->stage_classifier[i].count - 8; k += 8 )
{
stage_sum += icvEvalHidHaarClassifierAVX(
- cascade->stage_classifier[i].classifier+k,
+ cascade->stage_classifier[i].classifier + k,
variance_norm_factor, p_offset );
}
}
- #endif
- for(; k < cascade->stage_classifier[i].count; k++ )
- {
+#endif
+ for(; k < cascade->stage_classifier[i].count; k++ )
+ {
- stage_sum += icvEvalHidHaarClassifier(
- cascade->stage_classifier[i].classifier + k,
- variance_norm_factor, p_offset );
- }
+ stage_sum += icvEvalHidHaarClassifier(
+ cascade->stage_classifier[i].classifier + k,
+ variance_norm_factor, p_offset );
+ }
if( stage_sum < cascade->stage_classifier[i].threshold )
return -i;
}
}
- //_mm256_zeroupper();
return 1;
}
Size ssz(sum1.cols - 1 - winSize0.width, y2 - y1);
int x, y, ystep = factor > 2 ? 1 : 2;
- #ifdef HAVE_IPP
+#ifdef HAVE_IPP
if( cascade->hid_cascade->ipp_stages )
{
IppiRect iequRect = {equRect.x, equRect.y, equRect.width, equRect.height};
}
}
else
-#endif
+#endif // IPP
for( y = y1; y < y2; y += ystep )
for( x = 0; x < ssz.width; x += ystep )
{
#define ICV_HAAR_SIZE_NAME "size"
#define ICV_HAAR_STAGES_NAME "stages"
-#define ICV_HAAR_TREES_NAME "trees"
-#define ICV_HAAR_FEATURE_NAME "feature"
-#define ICV_HAAR_RECTS_NAME "rects"
-#define ICV_HAAR_TILTED_NAME "tilted"
-#define ICV_HAAR_THRESHOLD_NAME "threshold"
-#define ICV_HAAR_LEFT_NODE_NAME "left_node"
-#define ICV_HAAR_LEFT_VAL_NAME "left_val"
-#define ICV_HAAR_RIGHT_NODE_NAME "right_node"
-#define ICV_HAAR_RIGHT_VAL_NAME "right_val"
-#define ICV_HAAR_STAGE_THRESHOLD_NAME "stage_threshold"
-#define ICV_HAAR_PARENT_NAME "parent"
-#define ICV_HAAR_NEXT_NAME "next"
+#define ICV_HAAR_TREES_NAME "trees"
+#define ICV_HAAR_FEATURE_NAME "feature"
+#define ICV_HAAR_RECTS_NAME "rects"
+#define ICV_HAAR_TILTED_NAME "tilted"
+#define ICV_HAAR_THRESHOLD_NAME "threshold"
+#define ICV_HAAR_LEFT_NODE_NAME "left_node"
+#define ICV_HAAR_LEFT_VAL_NAME "left_val"
+#define ICV_HAAR_RIGHT_NODE_NAME "right_node"
+#define ICV_HAAR_RIGHT_VAL_NAME "right_val"
+#define ICV_HAAR_STAGE_THRESHOLD_NAME "stage_threshold"
+#define ICV_HAAR_PARENT_NAME "parent"
+#define ICV_HAAR_NEXT_NAME "next"
static int
icvIsHaarClassifier( const void* struct_ptr )
icvReadHaarClassifier, icvWriteHaarClassifier,
icvCloneHaarClassifier );
-#if 0
-namespace cv
-{
-
-HaarClassifierCascade::HaarClassifierCascade() {}
-HaarClassifierCascade::HaarClassifierCascade(const String& filename)
-{ load(filename); }
-
-bool HaarClassifierCascade::load(const String& filename)
-{
- cascade = Ptr<CvHaarClassifierCascade>((CvHaarClassifierCascade*)cvLoad(filename.c_str(), 0, 0, 0));
- return (CvHaarClassifierCascade*)cascade != 0;
-}
-
-void HaarClassifierCascade::detectMultiScale( const Mat& image,
- Vector<Rect>& objects, double scaleFactor,
- int minNeighbors, int flags,
- Size minSize )
-{
- MemStorage storage(cvCreateMemStorage(0));
- CvMat _image = image;
- CvSeq* _objects = cvHaarDetectObjects( &_image, cascade, storage, scaleFactor,
- minNeighbors, flags, minSize );
- Seq<Rect>(_objects).copyTo(objects);
-}
-
-int HaarClassifierCascade::runAt(Point pt, int startStage, int) const
-{
- return cvRunHaarClassifierCascade(cascade, pt, startStage);
-}
-
-void HaarClassifierCascade::setImages( const Mat& sum, const Mat& sqsum,
- const Mat& tilted, double scale )
-{
- CvMat _sum = sum, _sqsum = sqsum, _tilted = tilted;
- cvSetImagesForHaarClassifierCascade( cascade, &_sum, &_sqsum, &_tilted, scale );
-}
-
-}
-#endif
-
/* End of file. */
projects / platform / upstream / opencv.git / commitdiff